MERAL Myanmar Education Research and Learning Portal
-
RootNode
-
Co-operative College, Mandalay
-
Cooperative College, Phaunggyi
-
Co-operative University, Sagaing
-
Co-operative University, Thanlyin
-
Dagon University
-
Kyaukse University
-
Laquarware Technological college
-
Mandalay Technological University
-
Mandalay University of Distance Education
-
Mandalay University of Foreign Languages
-
Maubin University
-
Mawlamyine University
-
Meiktila University
-
Mohnyin University
-
Myanmar Institute of Information Technology
-
Myanmar Maritime University
-
National Management Degree College
-
Naypyitaw State Academy
-
Pathein University
-
Sagaing University
-
Sagaing University of Education
-
Taunggyi University
-
Technological University, Hmawbi
-
Technological University (Kyaukse)
-
Technological University Mandalay
-
University of Computer Studies, Mandalay
-
University of Computer Studies Maubin
-
University of Computer Studies, Meikhtila
-
University of Computer Studies Pathein
-
University of Computer Studies, Taungoo
-
University of Computer Studies, Yangon
-
University of Dental Medicine Mandalay
-
University of Dental Medicine, Yangon
-
University of Information Technology
-
University of Mandalay
-
University of Medicine 1
-
University of Medicine 2
-
University of Medicine Mandalay
-
University of Myitkyina
-
University of Public Health, Yangon
-
University of Veterinary Science
-
University of Yangon
-
West Yangon University
-
Yadanabon University
-
Yangon Technological University
-
Yangon University of Distance Education
-
Yangon University of Economics
-
Yangon University of Education
-
Yangon University of Foreign Languages
-
Yezin Agricultural University
-
New Index
-
Item
{"_buckets": {"deposit": "3a24491b-025e-4949-b387-b6eef9fc6532"}, "_deposit": {"id": "4597", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4597"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4597", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "An Efficient Tumor Segmentation of MRI Brain Images Using Thresholding and Morphology Operation", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "In medical image processing, segmentation of theinternal structure of brain is the fundamental task. Theprecise segmentation of brain tumor has great impact ondiagnosis, monitoring, treatment planning for patients.Various segmentation techniques are widely used for brainMagnetic Resonance Imaging (MRI). The aim of this paperpresents an efficient method of brain tumor segmentation.Morphological operation, pixel extraction threshold basedsegmentation and Gaussian high pass filter techniques areused in this paper. Thresholding is the simplest approach toseparate object from the background, and it is an efficienttechnique in medical image segmentation. Morphologyoperation can be used to extract region of brain tumor. Thissystem converts the RGB image to gray scale image andremoves the noise by using Gaussian high pass filter.Gaussian high pass filter produced sharpen image and thatimproves the contrast between bright and dark pixels. Thismethod will help physicians to identify the brain tumor beforeperforming the surgery."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Image segmentation"}, {"interim": "Thresholding"}, {"interim": "Morphology operation"}, {"interim": "Preprocessing"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-03-17"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "An Efficient Tumor Segmentation of MRI Brain Images Using Thresholding and Morphology Operation.pdf", "filesize": [{"value": "979 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 979000.0, "url": {"url": "https://meral.edu.mm/record/4597/files/An Efficient Tumor Segmentation of MRI Brain Images Using Thresholding and Morphology Operation.pdf"}, "version_id": "774024b8-0f2b-49d0-aa0f-3e5e2d757305"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Proceedings of the Eighteenth International Conference On Computer Applications (ICCA 2020)", "subitem_pages": "", "subitem_volume": ""}]}, "item_1583103147082": {"attribute_name": "Conference papers", "attribute_value_mlt": [{"subitem_acronym": "", "subitem_c_date": "", "subitem_conference_title": "", "subitem_part": "", "subitem_place": "", "subitem_session": "", "subitem_website": ""}]}, "item_1583103211336": {"attribute_name": "Books/reports/chapters", "attribute_value_mlt": [{"subitem_book_title": "", "subitem_isbn": "", "subitem_pages": "", "subitem_place": "", "subitem_publisher": ""}]}, "item_1583103233624": {"attribute_name": "Thesis/dissertations", "attribute_value_mlt": [{"subitem_awarding_university": "", "subitem_supervisor(s)": [{"subitem_supervisor": ""}]}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Myint, Hla Hla"}, {"subitem_authors_fullname": "Aung, Soe Lin"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2020-02-28"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "978-1-7281-5925-6"}, "item_title": "An Efficient Tumor Segmentation of MRI Brain Images Using Thresholding and Morphology Operation", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004597", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-03-17"}, "publish_date": "2020-03-17", "publish_status": "0", "recid": "4597", "relation": {}, "relation_version_is_last": true, "title": ["An Efficient Tumor Segmentation of MRI Brain Images Using Thresholding and Morphology Operation"], "weko_shared_id": -1}
An Efficient Tumor Segmentation of MRI Brain Images Using Thresholding and Morphology Operation
http://hdl.handle.net/20.500.12678/0000004597
http://hdl.handle.net/20.500.12678/000000459736603e8e-1a02-4ff1-a0f0-4ce5e71ab95c
3a24491b-025e-4949-b387-b6eef9fc6532
Name / File | License | Actions |
---|---|---|
![]() |
|
Publication type | ||||||
---|---|---|---|---|---|---|
Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | An Efficient Tumor Segmentation of MRI Brain Images Using Thresholding and Morphology Operation | |||||
Language | en | |||||
Publication date | 2020-02-28 | |||||
Authors | ||||||
Myint, Hla Hla | ||||||
Aung, Soe Lin | ||||||
Description | ||||||
In medical image processing, segmentation of theinternal structure of brain is the fundamental task. Theprecise segmentation of brain tumor has great impact ondiagnosis, monitoring, treatment planning for patients.Various segmentation techniques are widely used for brainMagnetic Resonance Imaging (MRI). The aim of this paperpresents an efficient method of brain tumor segmentation.Morphological operation, pixel extraction threshold basedsegmentation and Gaussian high pass filter techniques areused in this paper. Thresholding is the simplest approach toseparate object from the background, and it is an efficienttechnique in medical image segmentation. Morphologyoperation can be used to extract region of brain tumor. Thissystem converts the RGB image to gray scale image andremoves the noise by using Gaussian high pass filter.Gaussian high pass filter produced sharpen image and thatimproves the contrast between bright and dark pixels. Thismethod will help physicians to identify the brain tumor beforeperforming the surgery. | ||||||
Keywords | ||||||
Image segmentation, Thresholding, Morphology operation, Preprocessing | ||||||
Identifier | 978-1-7281-5925-6 | |||||
Journal articles | ||||||
Proceedings of the Eighteenth International Conference On Computer Applications (ICCA 2020) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |